In this project, I will be analysing a dataset of medical appointments to determine whether certain factors may be influencing whether a patient shows up for their scheduled appointment. This dataset contains over 100,000 medical appointments in Brazil from May 2016 (source: Kaggle). Python with Pandas, Numpy, Seaborn and Matplotlib libraries will be used for the data analysis.
https://www.kaggle.com/joniarroba/noshowappointments
- 20% of appointments in Brazil are no show appointments.
- Patients around 20 years old had a relatively high level of no shows whilst older patients (80+) had the highest attendance.
- Jardim Camburi had the highest number of no show appointments.
- Most neighbourhoods have around 15-25% of no shows, those with much higher or lower proportions generally had a smaller sample size.
- SMS does not appear to have an effect on no shows.
- Patients eligible for a scholarship were more likely to miss their appointment.
- Gender does not seem to have an effect on no shows.